Triple
T9051748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mon language |
E216899
|
entity |
| Predicate | scriptInfluenceOn |
P77309
|
FINISHED |
| Object | Burmese script |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Burmese script | Statement: [Mon language, scriptInfluenceOn, Burmese script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptInfluenceOn Context triple: [Mon language, scriptInfluenceOn, Burmese script]
-
A.
scriptInfluence
chosen
Indicates that one script affects, shapes, or alters the behavior, outcome, or characteristics of another entity (such as another script, process, or system).
-
B.
designInfluenceOn
Indicates that one design, designer, or design-related factor has an effect on shaping, guiding, or altering another design or design outcome.
-
C.
spinOffInfluence
Indicates that one entity has influenced the creation, direction, or characteristics of another entity that is derived from it as a spin-off.
-
D.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
-
E.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca83d362e88190ae44b4e4dc194209 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7a700de48190aa9f61d850e01cbd |
completed | April 1, 2026, 1:52 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee566b081909e3cdaf551dbd0ec |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:10 p.m.